Introduction
Visual attention allows observers to selectively process task-relevant information while filtering distracting stimuli. Classic behavioural studies have established the temporal limits of attentional selection, showing that attention can be deployed to multiple locations within 200 ms (Posner & Cohen, 1984; Eriksen & Eriksen, 1974). However, the neural mechanisms underlying these rapid shifts remain unclear. Event-related potentials offer millisecond-level temporal resolution, making them ideally suited to characterize the neural dynamics of attentional deployment.
Previous neuroimaging work using blocked-design fMRI has identified lateral prefrontal and posterior parietal regions active during attention tasks (Corbetta & Shulman, 1998). Whether these regions directly support the temporal binding of attention is unknown. The present study combines EEG recording with sophisticated source localization to establish the spatial and temporal characteristics of neural activity during selective visual attention.
Method
Participants
Thirty-two undergraduate students (mean age 21 years; 18 female) participated in exchange for course credit. All participants reported normal or corrected-to-normal vision and no history of neurological illness. Written informed consent was obtained prior to participation.
Procedure
Stimuli were presented on a computer monitor (60 Hz refresh rate) controlled by SuperLab 3.0 (Cedrus Corp.). Each trial began with a central fixation cross, followed 500 ms later by a directional cue (500 ms duration) pointing left or right. After a 200 ms cue-target interval, an array of eight small circles appeared for 100 ms, arranged in two rows of four. One circle contained a subtle luminance increment; participants reported the position (left or right visual field) and the presence or absence of the target via button press. There were 320 trials per session (160 valid cues, 160 invalid cues).
EEG was recorded continuously from 64 scalp electrodes (extended 10-20 system) at 500 Hz sampling rate using a Neuroscan system (Compumedics Ltd.). Electrode impedances were maintained below 5 kΩ. Data were referenced to linked mastoids and offline bandpass filtered (0.1 - 30 Hz). Epochs were extracted from -200 to +600 ms relative to cue onset. Ocular artifacts were corrected using independent components analysis. Trials with reaction times less than 200 ms or greater than 2000 ms were excluded from analysis.
Results
Behavioural performance was highly accurate (mean 94.2% correct, SD 3.8%). Reaction times were faster on valid-cue trials (M = 487 ms, SD = 112) compared to invalid-cue trials (M = 542 ms, SD = 128), t(31) = 3.47, p < .005. The magnitude of cueing effects correlated with the amplitude of the early ERP components, r = .52, p < .01.
Event-related potentials revealed a sustained negativity over frontocentral regions beginning 180 ms after cue onset and persisting until target presentation. This "cue-related negativity" (CRN) was larger over the hemisphere contralateral to the cued visual field. Peak amplitude at electrode Cz was 6.2 μV (SD 2.1), and the CRN showed both a vertex component and a lateral posterior component consistent with distributed processing. Source localization using LORETA indicated primary dipoles in the dorsolateral prefrontal cortex (Brodmann area 9/46) and precuneus.
Discussion
The present results provide neural evidence that visual attention engages a frontoparietal network that becomes tonically active during the preparation interval following a directional cue. The timing and topography of the cue-related negativity suggest that attentional control signals originate in prefrontal regions and modulate sensory processing areas via feedback connections. The strong correlation between ERP amplitude and behavioural cueing effects supports the functional relevance of this neural activity.
These findings extend previous fMRI work by establishing the temporal dynamics of attentional control with unprecedented precision. The sustained negativity observed in the 200-350 ms window likely reflects the consolidation of an attentional plan or the maintenance of a spatial representation. Further work combining EEG with computational modelling may clarify the mechanisms by which prefrontal regions exert control over posterior sensory areas.
References
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